scholarly journals Estimating Individualized Absolute Risk for Esophageal Squamous Cell Carcinoma: A Population-Based Study in High-Risk Areas of China

2021 ◽  
Vol 10 ◽  
Author(s):  
Yi Shen ◽  
Shuanghua Xie ◽  
Lei Zhao ◽  
Guohui Song ◽  
Yi Shao ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Relative Risk ◽  
High Risk ◽  
Esophageal Squamous Cell Carcinoma ◽  
Risk Model ◽  
Absolute Risk ◽  
Population Based ◽  
Risk Areas ◽  
Relative Risk Model

BackgroundEsophageal squamous cell carcinoma (ESCC) has a high incidence rate and poor prognosis. In this study, we aimed to develop a predictive model to estimate the individualized 5-year absolute risk for ESCC in Chinese populations living in the high-risk areas of China.MethodsWe developed a risk-predicting model based on the epidemiologic data from a population-based case-control study including 244 newly diagnosed ESCC patients and 1,220 healthy controls. Initially, we included easy-to-obtain risk factors to construct the model using the multivariable logistic regression analysis. The area under the ROC curves (AUC) with cross-validation methods was used to evaluate the performance of the model. Combined with local age- and sex-specific ESCC incidence and mortality rates, the model was then used to estimate the absolute risk of developing ESCC within 5 years.ResultsA relative risk model was established that included eight factors: age, sex, tobacco smoking, alcohol drinking, education, and dietary habits (intake of hot food, intake of pickled/salted food, and intake of fresh fruit). The relative risk model had good discrimination [AUC, 0.785; 95% confidence interval (CI), 0.749–0.821]. The estimated 5-year absolute risk of ESCC for individuals varied widely, from 0.0003% to 19.72% in the studied population, depending on the exposure to risk factors.ConclusionsOur model based on readily identifiable risk factors showed good discriminative accuracy and strong robustness. And it could be applied to identify individuals with a higher risk of developing ESCC in the Chinese population, who might benefit from further targeted screening to prevent esophageal cancer.

scholarly journals Mycotoxin exposure is associated with increased risk of esophageal squamous cell carcinoma in Huaian area, China

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Kathy S. Xue ◽  
Lili Tang ◽  
Guiju Sun ◽  
Shaokang Wang ◽  
Xu Hu ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Population Based ◽  
Additive Interaction ◽  
Exposure Biomarker ◽  
Increased Risk ◽  
Risk Areas

Abstract Background Consumption of moldy food has previously been identified as a risk factor for esophageal squamous cell carcinoma (ESCC) in high-risk countries; however, what contributing roles these dietary carcinogenic mycotoxins play in the etiology of ESCC are largely unknown. Methods A mycotoxin biomarker-incorporated, population-based case-control study was performed in Huaian area, Jiangsu Province, one of the two high-risk areas in China. Exposure biomarkers of aflatoxins (AF) and fumonisins (FN) were quantitatively analyzed using HPLC-fluorescence techniques. Results Among the cases (n = 190), the median levels of AF biomarker, serum AFB1-lysine adduct, and FN biomarker, urinary FB1, were 1.77 pg/mg albumin and 176.13 pg/mg creatinine, respectively. Among the controls (n = 380), the median levels of AFB1-lysine adduct and urinary FB1 were 1.49 pg/mg albumin and 56.92 pg/mg creatinine, respectively. These mycotoxin exposure biomarker levels were significantly higher in cases as compared to controls (p <  0.05 and 0.01, respectively). An increased risk to ESCC was associated with exposure to both AFB1 and FB1 (p <  0.001 for both). Conclusions Mycotoxin exposure, especially to AFB1 and FB1, was associated with the risk of ESCC, and a greater-than-additive interaction between co-exposures to these two mycotoxins may contribute to the increased risk of ESCC in Huaian area, China.

scholarly journals A nomogram for screening esophageal squamous cell carcinoma based on environmental risk factors in a high-incidence area of China: a population-based case-control study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaorong Yang ◽  
Chen Suo ◽  
Tongchao Zhang ◽  
Xiaolin Yin ◽  
Jinyu Man ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Esophageal Squamous Cell Carcinoma ◽  
Case Control Study ◽  
Population Based ◽  
Case Control ◽  
Endoscopic Screening ◽  
Weighted Analysis ◽  
Control Study

Abstract Background Selection of high-risk subjects for endoscopic screening of esophageal squamous cell carcinoma (ESCC) lacks individual predictive tools based on environmental risk factors. Methods We performed a large population-based case-control study of 1418 ESCC cases and 1992 controls in a high-risk area of China. Information on potential risk factors was collected via face-to-face interview using an electronic structured questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression models, and predictive nomograms were established accordingly. A weighted analysis was further conducted to introduce age into predictive nomograms due to frequency matching study design. Results Most cases were usually exposed to 4 to 6 risk factors, but most controls were usually exposed to 3 to 5 risk factors. The AUCs of male and female predictive nomograms were 0.75 (95%CI: 0.72, 0.77) and 0.76 (95%CI: 0.73, 0.79), respectively. The weighted analysis adding age in the predictive model improved the AUC in both men and women (0.81 (95%CI: 0.79, 0.84) and 0.88 (95%CI: 0.85, 0.90), respectively). Conclusions An easy-to-use preclinical predictive tool is provided to select candidate population with high ESCC risk for endoscopic screening. Its usefulness needs to be further evaluated in future screening practice.

scholarly journals Cooking Methods and Esophageal Squamous Cell Carcinoma in High-Risk Areas of Iran

2013 ◽  
Vol 66 (3) ◽  
pp. 500-505 ◽  
Author(s):  
Roya Hakami ◽  
Arash Etemadi ◽  
Farin Kamangar ◽  
Akram Pourshams ◽  
Javad Mohtadinia ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cooking Methods ◽  
Risk Areas

scholarly journals Geographical distribution of risk factors for invasive non-typhoidal Salmonella at the subnational boundary level in sub-Saharan Africa

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jung-Seok Lee ◽  
Vittal Mogasale ◽  
Florian Marks ◽  
Jerome Kim
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Case Fatality ◽  
Population Based ◽  
Sub Saharan Africa ◽  
Health Concern ◽  
Risk Level ◽  
Accurate Estimation ◽  
Risk Areas ◽  
Sub Saharan

Abstract Background Invasive non-typhoidal Salmonella (iNTS) is a growing health-concern in many parts of sub-Saharan Africa. iNTS is associated with fatal diseases such as HIV and malaria. Despite high case fatality rates, the disease has not been given much attention. The limited number of population-based surveillance studies hampers accurate estimation of global disease burden. Given the lack of available evidence on the disease, it is critical to identify high risk areas for future surveillance and to improve our understanding of iNTS endemicity. Methods Considering that population-based surveillance data were sparse, a composite index called the iNTS risk factor (iNRF) index was constructed based on risk factors that commonly exist across countries. Four risk factors associated with the prevalence of iNTS were considered: malaria, HIV, malnutrition, and safe water. The iNRF index was first generated based on the four risk factors which were collected within a 50 km radius of existing surveillance sites. Pearson product-moment correlation was used to test statistical associations between the iNRF index and the prevalence of iNTS observed in the surveillance sites. The index was then further estimated at the subnational boundary level across selected countries and used to identify high risk areas for iNTS. Results While the iNRF index in some countries was generally low (i.e. Rwanda) or high (i.e. Cote d’Ivoire), the risk-level of iNTS was variable not only by country but also within a country. At the provincial-level, the highest risk area was identified in Maniema, the Democratic Republic of Congo, whereas Dakar in Senegal was at the lowest risk. Conclusions The iNRF index can be a useful tool to understand the geographically varying risk-level of iNTS. Given that conducting a population-based surveillance study requires extensive human and financial resources, identifying high risk areas for iNTS prior to a study implementation can facilitate an appropriate site-selection process in the future.

scholarly journals A nomogram to predict lymph node metastasis risk for early esophageal squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaofeng Duan ◽  
Xiaobin Shang ◽  
Jie Yue ◽  
Zhao Ma ◽  
Chuangui Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Squamous Cell Carcinoma ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Early Stage ◽  
Derivation Cohort ◽  
Node Metastasis

Abstract Background A nomogram was developed to predict lymph node metastasis (LNM) for patients with early-stage esophageal squamous cell carcinoma (ESCC). Methods We used the clinical data of ESCC patients with pathological T1 stage disease who underwent surgery from January 2011 to June 2018 to develop a nomogram model. Multivariable logistic regression was used to confirm the risk factors for variable selection. The risk of LNM was stratified based on the nomogram model. The nomogram was validated by an independent cohort which included early ESCC patients underwent esophagectomy between July 2018 and December 2019. Results Of the 223 patients, 36 (16.1%) patients had LNM. The following three variables were confirmed as LNM risk factors and were included in the nomogram model: tumor differentiation (odds ratio [OR] = 3.776, 95% confidence interval [CI] 1.515–9.360, p = 0.004), depth of tumor invasion (OR = 3.124, 95% CI 1.146–8.511, p = 0.026), and tumor size (OR = 2.420, 95% CI 1.070–5.473, p = 0.034). The C-index was 0.810 (95% CI 0.742–0.895) in the derivation cohort (223 patients) and 0.830 (95% CI 0.763–0.902) in the validation cohort (80 patients). Conclusions A validated nomogram can predict the risk of LNM via risk stratification. It could be used to assist in the decision-making process to determine which patients should undergo esophagectomy and for which patients with a low risk of LNM, curative endoscopic resection would be sufficient.

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